Death from metastatic prostate cancer (mPC) is projected to increase from 375,000 in 2020 to 700,000 in 2040 globally.  There is an urgent need to develop new treatments for mPC. Several failed phase 3 trials have shown a limited role of immune check point inhibitor either as single agent or in combination for mPC. With the development of targeted radioligand therapies, bispecific T cell engagers (BiTEs), antibody drug conjugates and chimeric antigen receptor T cell (CAR T) therapies, tumor associated cell surface antigens have emerged as new therapeutic targets in mPC. Here we will discuss ongoing and completed clinical trials testing BiTEs and CAR T to target prostate-specific membrane antigen (PSMA), six transmembrane epithelial antigen of the prostate 1 (STEAP1), kallikrein related peptidase 2 (KLK2), prostate stem cell antigen (PSCA) and delta-like protein 3 (DLL3) in mPC. Pros and cons of different treatment strategies and future directions on sequential or combinational therapy will also be discussed.

Cancer progression and therapeutic resistance are closely linked to a stemness phenotype. Here, we introduce a protein expression-based stemness index (PROTsi) to evaluate oncogenic dedifferentiation in relation to histopathology, molecular features, and clinical outcomes. Utilizing datasets from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) across eleven tumor types, we validate PROTsi’s effectiveness in accurately quantifying stem-like features. Through integration of PROTsi with multi-omics, including protein post-translational modifications, we identified molecular features associated with stemness and proteins that act as active nodes within transcriptional networks, driving tumor aggressiveness. Proteins highly correlated with stemness were identified as potential drug targets both shared and tumor-specific. These stemness-associated proteins demonstrate predictive value for clinical outcomes, as confirmed by immunohistochemistry in multiple samples. The findings emphasize PROTsi’s efficacy as a valuable tool for selecting predictive protein targets, a crucial step in customizing anti-cancer therapy and advancing the clinical development of cures for cancer patients.

Adolescents and young adults (AYAs) aged 15-39 are experiencing a rise in cancer incidences, potentially leading to the next global epidemic. Despite high survival rates, AYA cancer survivors face long-term health effects. Nanomedicine, particularly nano-therapeutics and diagnostic tools, offers hope through immunomodulation, targeting cancer cells, the tumor microenvironment, and the immune system, enhancing drug delivery and diagnostics. Multi-omics strategies and nanoinformatics are advancing cancer immunotherapy, with a focus on personalized treatment.

The increasing trend and survival rates of AYA cancers impact the most in South and East Asia, bearing the highest national medical burden. Early-onset cancers show positive results to immunotherapy making it a trending option in cancer management. However, individual treatment outcomes vary, and there is a need for combined immunotherapies to optimize results. The development of interdisciplinary experts is crucial for analyzing multi-modal data, with a focus on data privacy and security.

Tumour immunomics is set to dominate future cancer treatments, with big data playing a key role in understanding immune-related adverse events (irAEs) and accelerating research. This will improve clinical management of AYA patients on immunotherapy, leading to better outcomes and a new era of personalized nanomedicine. The empowerment of tumour immunomics is essential for translating nanotherapeutic discoveries into practical applications, leading to promising transformative results for cancer treatment.

Yet, the translation journey is hindered by the many stages of development across different methodologies. Also, the widening chasm between our ability to generate vast amounts of data and our capacity to process it set limitations to clinical applications. Scalability and cost-effectiveness must be considered from experimental stages to smoothen trial designs and recruitment outcomes.

Nearly 1 out of every 8 women will develop breast cancer during her lifetime, making breast cancer the most common noncutaneous malignancy in women, particularly among the Hispanic/Latino population. Hispanic/Latino women are more likely than non-Hispanic/Latino women to be diagnosed with breast cancer after the disease has progressed to a fatal stage. This quantitative study measured how knowledge, attitude, and screening practices affect the prevalence and outcomes of breast cancer cases among Hispanic/Latino women while controlling for socioeconomic status factors, using social cognitive theory as a framework. This research uses secondary data analysis of a cross-sectional survey study, the 2014 Health Information National Trends Survey, which collected pertinent breast cancer health information on the Hispanic/Latino population in the United States. Descriptive characteristics were derived from a sample population of 3,677, a logistic regression analysis model was used to compute crude odds ratio and confidence interval. The findings revealed that Hispanic/Latino women had a positive attitude toward information sources such as physicians and medical facilities; however, the findings indicate Hispanic/Latino women had negative attitude when these individuals lacked information sources. There were notable differences in how frequently Hispanic/Latino women access screening practices, due to income, knowledge, culture, and attitudes toward a health condition like breast cancer. The findings revealed an opportunity for health professionals to promote breast cancer awareness by educating Hispanic/Latino women about the importance of screening practices and behavioral compliance to reduce their late-stage diagnoses of breast cancer.